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首页> 外文期刊>Operations Research: The Journal of the Operations Research Society of America >A LITTLES RESULT APPROACH TO THE SERVICE CONSTRAINED SPARES PROVISIONING PROBLEM FOR REPAIRABLE ITEMS
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A LITTLES RESULT APPROACH TO THE SERVICE CONSTRAINED SPARES PROVISIONING PROBLEM FOR REPAIRABLE ITEMS

机译:可维修项目的服务约束备件供应问题的小结果方法

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摘要

A set of identical machines are deployed to meet a known and constant demand. If a machine fails, a replacement part must be available before repair of the machine may be initiated. If the part is currently out of stock, it must be ordered. Once repaired at one of a finite number of repair stations, the machine serves as an ''operational ready'' standby if demand is currently being met; otherwise, the machine is immediately deployed. Machine time-to-failure, ordering leadtimes, and repair times are all assumed to be exponentially distributed. The objective is to determine the number of machines and repair channels that minimize a cost function subject to the service constraint; i.e., on average, the number of machines operating should be at least some fraction of the demand. We present an algorithm that efficiently generates all the boundary points of the feasible region, from which the optimal solution is readily identified, for the special cases in which there is either zero or infinite stock. Use of the algorithm, which is based upon Little's result and first-passage time analysis, requires negligible storage and computational effort. In fact, for problems of moderate size, computation of optimal solutions via a nonprogrammable pocket calculator is feasible. [References: 21]
机译:部署了一组相同的机器来满足已知且持续的需求。如果机器出现故障,则必须先准备好更换零件,然后才能开始修理机器。如果零件当前无货,则必须订购。一旦在有限数量的维修站之一进行维修,如果当前满足需求,则该机器将作为“运行就绪”备用机器;否则,计算机将立即部署。机器的故障时间,订购的交货时间和维修时间均假定为指数分布。目的是确定机器和维修渠道的数量,以使受服务约束的成本函数最小化;也就是说,平均而言,运行的机器数量至少应是需求的一部分。对于存在零或无限库存的特殊情况,我们提出了一种算法,该算法可以有效地生成可行区域的所有边界点,从中容易找到最佳解决方案。基于Little的结果和首次通过时间分析的算法的使用需要很少的存储和计算工作。实际上,对于中等大小的问题,通过不可编程的袖珍计算器计算最佳解是可行的。 [参考:21]

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